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陈科研 committed Nov 26, 2023
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Expand Up @@ -333,14 +333,14 @@ python zero_to_fp32.py . $SAVE_CHECKPOINT_NAME -t $CHECKPOINT_DIR # $SAVE_CHECK

这里我们列出了使用不同模型的资源消耗情况,供您参考。

| 模型名称 | 骨干网络类型 | 图像尺寸 | GPU | Batch Size | 加速策略 | 单卡显存占用 |
|:---------------------:|:--------:| :------: |:-----------------:|:----------:|:----------------:|:-------:|
| SAM-seg (Mask R-CNN) | ViT-B/16 | 1024x1024 | 1x RTX 4090 24G | 8 | AMP FP16 | 19.4 GB |
| SAM-seg (Mask2Former) | ViT-B/16 | 1024x1024 | 1x RTX 4090 24G | 8 | AMP FP16 | 21.5 GB |
| SAM-det | ResNet50 | 1024x1024 | 1x RTX 4090 24G | 8 | FP32 | 16.6 GB |
| RSPrompter-anchor | ViT-B/16 | 1024x1024 | 1x RTX 4090 24G | 2 | AMP FP16 | 20.9 GB |
| RSPrompter-query | ViT-B/16 | 1024x1024 | 1x RTX 4090 24G | 1 | AMP FP16 | OOM |
| RSPrompter-query | ViT-B/16 | 1024x1024 | 8x RTX 4090 24G | 1 | DeepSpeed ZeRO-2 | OOM |
| 模型名称 | 骨干网络类型 | 图像尺寸 | GPU | Batch Size | 加速策略 | 单卡显存占用 |
|:---------------------:|:--------:| :------: |:------------------:|:----------:|:----------:|:-------:|
| SAM-seg (Mask R-CNN) | ViT-B/16 | 1024x1024 | 1x RTX 4090 24G | 8 | AMP FP16 | 19.4 GB |
| SAM-seg (Mask2Former) | ViT-B/16 | 1024x1024 | 1x RTX 4090 24G | 8 | AMP FP16 | 21.5 GB |
| SAM-det | ResNet50 | 1024x1024 | 1x RTX 4090 24G | 8 | FP32 | 16.6 GB |
| RSPrompter-anchor | ViT-B/16 | 1024x1024 | 1x RTX 4090 24G | 2 | AMP FP16 | 20.9 GB |
| RSPrompter-query | ViT-B/16 | 1024x1024 | 1x RTX 4090 24G | 1 | AMP FP16 | OOM |
| RSPrompter-query | ViT-B/16 | 1024x1024 | 8x NVIDIA A100 40G | 1 | ZeRO-2 | 39.6 GB |



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